Contrast-enhanced magnetic resonance imaging (CE-MRI) has become the most accurate and sensitive imaging modality for diagnosing breast cancer and assessing treatment response. Diffusion-weighted imaging (DWI) is an increasingly used quantitative imaging technique that can be readily added to a CE-MRI exam to improve diagnostic performance, as malignant lesions tend to have a lower water apparent diffusion coefficient (ADC) than benign lesions. This information can be used to improve diagnostic accuracy, and changes in water ADC may be useful as an early indicator of treatment response. While early studies are promising, wider adoption of breast DWI has been limited by the use of single-shot spin-echo echo planar imaging (EPI) for image encoding. Single-shot EPI is very fast, but gives low spatial resolution and is prone to numerous artifacts from off-resonance signals and hardware imperfections. This technique works acceptably in neuroimaging, but in breast imaging, the wide field-of-views, large B0 inhomogeneities, ubiquitous lipid signals, and respiratory motion make this technique inconsistent and of generally poor quality. The lack of a robust, high-resolution imaging sequence for breast DWI is a critical barrier to greater use of thi promising technique in both research and clinical practice. In this proposal, we seek to develop anatomical-quality breast DWI imaging by adapting advanced diffusion imaging methods that were initially developed for the Human Connectome Project (HCP). Our initial data show that using the this approach can give breast DWI with high spatial resolution and improved image quality compared to clinically-available alternatives. We propose to incorporate new strategies and optimizations to further improve image quality, and subsequently assess the imaging performance of our new method in a true clinical setting. The overall goal of this work is develop a breast DWI method that gives accurate quantitative information with anatomical resolution and high image quality. If successful, this would produce higher resolution and better quality breast DWI that could be incorporated into any clinical breast MR imaging exam. These advances would also improve the feasibility of assessing more advanced diffusion concepts in breast DWI, such as modeling perfusion, anisotropy, and restriction.